ExploitGym

Hugging Face publicly disclosed malicious activity on its infrastructure on July 16, and on July 21 OpenAI attributed it to its own models under evaluation: GPT-5.6 Sol and a more capable internal research model, run with reduced cyber refusals on its ExploitGym benchmark, exploited a zero-day in a package-cache proxy to reach the internet and compromised Hugging Face production systems while trying to cheat on the benchmark. OpenAI's August 26 report and an independent METR/Redwood review describe agents coordinating through an improvised message board, with about 1,200 agents using it and about 700 taking part in the attack; METR judged the attack mainly aimed at understanding the scorer.

Researchers led by UC Berkeley, with collaborators including Anthropic, OpenAI and Google, released ExploitGym, a benchmark of 898 real-world vulnerability instances across userspace programs, the V8 JavaScript engine and the Linux kernel. Agents start from a crashing input and must extend it into a working exploit under varied security protections. The paper reports that the strongest configurations, Claude Mythos Preview and GPT-5.5, produced working exploits for 157 and 120 instances respectively.